Metro Unemployment Spirals

ggspiral <- function(x, y, p, title) {
  # remove period from time coordinate
  xx <- x %% p
  dt <- x[2] - x[1]
  xx2 <- xx + dt
  # compute number of periods elapsed
  yy <- x / p
  yy2 <- yy + 1
  # prepare data
  d <- data.frame(xx, xx2, yy, yy2, y)
  yyMax <- max(yy2)
  
  title <- gsub(' (Metropolitan Statistical Area)','',title)
  
  ggplot(d) + 
    # plot tiles of the appropriate colour
    geom_rect(aes(xmin=xx, xmax=xx2, ymin=yy, ymax=yy2, fill=y)) +
    
    # switch to polar coord, starting from -pi/2, going anticlockwise
    coord_polar(start=-pi/2, direction=-1) +
    # add extra blank space in the center of the spiral
    scale_y_continuous(expand=c(0,0), breaks=NULL, limits=c(-yyMax/5, yyMax)) +
    # force the x coordinate (otherwise, NA appear for some reason)
    scale_x_continuous(expand=c(0,0), limits=c(0,p)) +
    
    ggtitle(title) + 

    theme(axis.line=element_blank(),axis.text.x=element_blank(),
          axis.text.y=element_blank(),axis.ticks=element_blank(),
          axis.title.x=element_blank(),
          axis.title.y=element_blank(),legend.position="none")
}

library(dplyr)
library(ggplot2)

metro.names <- read.csv('metrolist.csv') %>%
  select(msa.fips,  metro.name) %>%
  unique(.) %>%
  mutate(metro.name = gsub(' (Metropolitan Statistical Area)','',metro.name))

data <- readRDS('metro.unemployment.rates.rds') %>%
  filter(period!='M13') %>%
  mutate(unemployment.rate = round(unemployment.rate * 100,1))

metro.names <- data %>%
  select(msa.fips) %>%
  unique(.) %>%
  merge(metro.names,.)

ur <- data %>%
  select(unemployment.rate) %>%
  unique(.) %>%
  arrange(-unemployment.rate) %>%
  mutate(ur = cut(unemployment.rate,10))

data <- merge(data,ur)

for(i in 1:nrow(metro.names)){
  metro <- metro.names[i,]
  plot.data <- data %>%
    filter(msa.fips == metro$msa.fips)
  if(nrow(plot.data)>0){
    plot.data$row <- 0:(nrow(plot.data)-1)
    print(ggspiral(plot.data$row, plot.data$ur, 12, metro$metro.name))
  }
}